[Doc] Update docs and dockerfiles for rebase of vllm v0.18.0 (#2038)
Signed-off-by: tzhouam <tzhouam@connect.ust.hk> Signed-off-by: Gao Han <hgaoaf@connect.ust.hk> Co-authored-by: Gao Han <hgaoaf@connect.ust.hk>
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Zhou TaichangandGao Han authored and GitHub committed
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@@ -10,7 +10,7 @@ steps:
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DOCKER_BUILDKIT: "1"
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# Buildkite will automatically replace this with the actual commit hash
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VLLM_IMAGE_TAG: "${BUILDKITE_COMMIT}"
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VLLM_VERSION: "v0.17.0"
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VLLM_VERSION: "v0.18.0"
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priority: 100
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timeout_in_minutes: 60
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soft_fail: true
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+4
-23
@@ -1,5 +1,5 @@
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ARG VLLM_BASE_IMAGE=vllm/vllm-openai
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ARG VLLM_BASE_TAG=v0.17.0
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ARG VLLM_BASE_TAG=v0.18.0
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FROM ${VLLM_BASE_IMAGE}:${VLLM_BASE_TAG}
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ARG APP_DIR=/workspace/vllm-omni
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WORKDIR ${APP_DIR}
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@@ -11,29 +11,10 @@ RUN apt-get update && \
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apt-get clean && \
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rm -rf /var/lib/apt/lists/*
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RUN uv pip uninstall --system -y vllm || true
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# Install vllm-omni into the same uv-managed Python environment used by the base image.
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# Use bash -c so that $(python3 -c ...) is expanded inside the container.
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RUN uv pip install --system --no-cache-dir ".[dev]"
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# Install vLLM from precompiled wheel at the selected commit.
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# Must use direct URL because the wheel has a PEP 440 local version identifier
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# (e.g. +g0a0a1a198) which pip/uv refuse to install from a PEP 503 package index.
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ENV VLLM_PRECOMPILED_WHEEL_COMMIT=89138b21cc246ae944c741d5c399c148e2b770ab
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RUN VLLM_WHEEL_URL=$(python3 -c "import urllib.request,re; \
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html=urllib.request.urlopen('https://wheels.vllm.ai/${VLLM_PRECOMPILED_WHEEL_COMMIT}/vllm/').read().decode(); \
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m=re.search(r'>(\S+x86_64\.whl)<',html); \
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print('https://wheels.vllm.ai/${VLLM_PRECOMPILED_WHEEL_COMMIT}/'+m.group(1).replace('+','%2B'))") && \
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echo "Installing vLLM from: ${VLLM_WHEEL_URL}" && \
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uv pip install --system --force-reinstall "${VLLM_WHEEL_URL}"
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RUN uv pip install --system ".[dev]"
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RUN uv pip install --system --upgrade \
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"flashinfer-cubin==0.6.6" \
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"nvidia-cublas-cu12==12.9.1.4" \
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"numpy==2.2.6"
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RUN uv pip install --system --upgrade \
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"flashinfer-jit-cache==0.6.6" \
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--index-url https://flashinfer.ai/whl/cu129
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RUN ln -sf /usr/bin/python3 /usr/bin/python
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ENTRYPOINT []
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@@ -1,4 +1,4 @@
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ARG BASE_IMAGE=vllm/vllm-openai-rocm:v0.17.0
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ARG BASE_IMAGE=vllm/vllm-openai-rocm:v0.18.0
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FROM ${BASE_IMAGE} AS base
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# Declare a variable to know if we want to use the nightly build or the stable build.
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@@ -10,7 +10,7 @@ FROM ${BASE_IMAGE} AS base
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# we should swap over to use stable release ASAP.
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# We should avoid relying on custom commits.
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ARG USE_NIGHTLY_BUILD=0
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ARG VLLM_VERSION_OR_COMMIT_HASH=2d5be1dd5ce2e44dfea53ea03ff61143da5137eb
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ARG VLLM_VERSION_OR_COMMIT_HASH=89138b21cc246ae944c741d5c399c148e2b770ab
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ARG ARG_PYTORCH_ROCM_ARCH
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ENV PYTORCH_ROCM_ARCH=${ARG_PYTORCH_ROCM_ARCH:-${PYTORCH_ROCM_ARCH}}
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@@ -76,7 +76,7 @@ ENV UV_EXTRA_INDEX_URL=${PIP_EXTRA_INDEX_URL}
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ENV UV_INDEX_STRATEGY="unsafe-best-match"
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ENV UV_LINK_MODE="copy"
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ARG VLLM_VERSION=v0.17.0
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ARG VLLM_VERSION=v0.18.0
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RUN git clone -b ${VLLM_VERSION} https://github.com/vllm-project/vllm
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WORKDIR /workspace/vllm
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@@ -30,7 +30,7 @@ vLLM-Omni is a Python library that supports the following GPU variants. The libr
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### Pre-built wheels
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Note: Pre-built wheels are currently only available for vLLM-Omni 0.11.0rc1, 0.12.0rc1, 0.14.0rc1, 0.14.0, 0.16.0. For the latest version, please [build from source](https://docs.vllm.ai/projects/vllm-omni/en/latest/getting_started/installation/gpu/#build-wheel-from-source).
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Note: Pre-built wheels are currently available for vLLM-Omni 0.11.0rc1, 0.12.0rc1, 0.14.0rc1, 0.14.0, 0.16.0, and 0.18.0. If you need a newer unreleased revision, please [build from source](https://docs.vllm.ai/projects/vllm-omni/en/latest/getting_started/installation/gpu/#build-wheel-from-source).
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=== "NVIDIA CUDA"
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@@ -34,13 +34,13 @@ uv pip install vllm-omni
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# --8<-- [start:build-wheel-from-source]
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#### Installation of vLLM
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If you do not need to modify source code of vLLM, you can directly install the stable 0.17.0 release version of the library
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If you do not need to modify source code of vLLM, you can directly install the stable 0.18.0 release version of the library
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```bash
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uv pip install vllm==0.17.0 --torch-backend=auto
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uv pip install vllm==0.18.0 --torch-backend=auto
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```
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The release 0.17.0 of vLLM is based on PyTorch 2.10.0 which requires CUDA 12.9 environment.
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The 0.18.0 release of vLLM ships CUDA 12.9-compatible binaries by default. If you need a different CUDA variant or want to reuse an existing PyTorch installation, build vLLM from source instead.
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#### Installation of vLLM-Omni
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Since vllm-omni is rapidly evolving, it's recommended to install it from source
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@@ -56,11 +56,11 @@ If you want to check, modify or debug with source code of vLLM, install the libr
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```bash
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git clone https://github.com/vllm-project/vllm.git
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cd vllm
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git checkout v0.17.0
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git checkout v0.18.0
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```
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Set up environment variables to get pre-built wheels. If there are internet problems, just download the whl file manually. And set `VLLM_PRECOMPILED_WHEEL_LOCATION` as your local absolute path of whl file.
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```bash
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export VLLM_PRECOMPILED_WHEEL_LOCATION=https://github.com/vllm-project/vllm/releases/download/v0.17.0/vllm-0.17.0-cp38-abi3-manylinux_2_31_x86_64.whl
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export VLLM_PRECOMPILED_WHEEL_LOCATION=https://github.com/vllm-project/vllm/releases/download/v0.18.0/vllm-0.18.0+cu129-cp38-abi3-manylinux_2_35_x86_64.whl
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```
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Install vllm with command below (If you have no existing PyTorch).
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```bash
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@@ -91,7 +91,7 @@ docker run --runtime nvidia --gpus 2 \
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--env "HF_TOKEN=$HF_TOKEN" \
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-p 8091:8091 \
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--ipc=host \
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vllm/vllm-omni:v0.16.0 \
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vllm/vllm-omni:v0.18.0 \
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--model Qwen/Qwen3-Omni-30B-A3B-Instruct --port 8091
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```
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@@ -13,7 +13,7 @@ vLLM-Omni current recommends the steps in under setup through Docker Images.
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vLLM-Omni is built based on vLLM. Please install it with command below.
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```bash
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uv pip install vllm==0.17.0+rocm700 --extra-index-url https://wheels.vllm.ai/rocm/0.17.0/rocm700
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uv pip install vllm==0.18.0+rocm700 --extra-index-url https://wheels.vllm.ai/rocm/0.18.0/rocm700
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```
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#### Installation of vLLM-Omni
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@@ -34,13 +34,13 @@ uv pip install onnxruntime-rocm sox
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# --8<-- [start:build-wheel-from-source]
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#### Installation of vLLM
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If you do not need to modify source code of vLLM, you can directly install the stable 0.17.0 release version of the library
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If you do not need to modify source code of vLLM, you can directly install the stable 0.18.0 release version of the library
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```bash
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uv pip install vllm==0.17.0+rocm700 --extra-index-url https://wheels.vllm.ai/rocm/0.17.0/rocm700
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uv pip install vllm==0.18.0+rocm700 --extra-index-url https://wheels.vllm.ai/rocm/0.18.0/rocm700
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```
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The release 0.17.0 of vLLM requires ROCm 7.0 environment.
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The pre-built 0.18.0 vLLM wheel targets ROCm 7.0. If you need a different ROCm stack or want to reuse an existing PyTorch installation, build vLLM from source instead.
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#### Installation of vLLM-Omni
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Since vllm-omni is rapidly evolving, it's recommended to install it from source
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@@ -58,7 +58,7 @@ If you want to check, modify or debug with source code of vLLM, install the libr
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```bash
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git clone https://github.com/vllm-project/vllm.git
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cd vllm
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git checkout v0.17.0
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git checkout v0.18.0
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python3 -m pip install -r requirements/rocm.txt
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python3 setup.py develop
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```
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@@ -130,7 +130,7 @@ docker run --rm \
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-v ~/.cache/huggingface:/root/.cache/huggingface \
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--env "HF_TOKEN=$HF_TOKEN" \
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-p 8091:8091 \
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vllm/vllm-omni-rocm:v0.16.0 \
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vllm/vllm-omni-rocm:v0.18.0 \
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--model Qwen/Qwen3-Omni-30B-A3B-Instruct --omni --port 8091
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```
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@@ -149,7 +149,7 @@ docker run --rm -it \
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-v ~/.cache/huggingface:/root/.cache/huggingface \
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--env "HF_TOKEN=$HF_TOKEN" \
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--entrypoint bash \
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vllm/vllm-omni-rocm:v0.16.0
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vllm/vllm-omni-rocm:v0.18.0
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```
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# --8<-- [end:pre-built-images]
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@@ -19,10 +19,10 @@ uv venv --python 3.12 --seed
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source .venv/bin/activate
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# On CUDA
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uv pip install vllm==0.17.0 --torch-backend=auto
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uv pip install vllm==0.18.0 --torch-backend=auto
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# On ROCm
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uv pip install vllm==0.17.0 --extra-index-url https://wheels.vllm.ai/rocm/0.17.0/rocm700
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uv pip install vllm==0.18.0+rocm700 --extra-index-url https://wheels.vllm.ai/rocm/0.18.0/rocm700
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git clone https://github.com/vllm-project/vllm-omni.git
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cd vllm-omni
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